Seismic traveltime data and well marker data are integrated in many petroleum reservoirs for improved knowledge of oil-in-place, hydrocarbon heterogeneities, risk evaluation, and in general for making better decisions about both drilling and drainage strategies. The way seismic and well data are integrated differs dramatically and depends heavily on the main objective of study. To obtain the best out of the data, one must take into account the uncertainty associated with each data type. Consider for instance the thickness of an oil reservoir; One data source (wells) tells you it is 30 m, the second (seismic) says 50 m. How much is this reservoir worth in terms of net present value? Should we start producing hydrocarbons? If the critical thickness based on the cost and expected revenues is 40 m, we would have to trust the first source less than the second to start production.
Seismic data are acquired by emitting sound from a source such as an air gun and then monitoring the reflected signal at a set of receivers. There is a huge literature on converting such reflection data to a structural model for the subsurface, represented in (east, north and depth) coordinates. The most common method is to process manually picked reflection times (traveltimes) from main geological interfaces by collecting them to fixed surface reference positions, and then stretching the traveltimes (measured in seconds) according to a priori known velocity. One caveat with this method is its lack of ability to capture the three dimensional uncertainty in the structural model. Another is the implicit assumption that each surface reference point represents a reflection point directly underneath, and not from another reflector to the east or north of the surface location. The second assumption (referred to as ‘vertical stretch’ since only the depth dimension is influenced in the structural imaging) can be bypassed with more complicated depth conversion methods, for instance by using ray tracing, but the problem of capturing the three dimensional structural uncertainty remains.
Well marker data consists of geographical (east, north, depth) picks as the well goes through a geological marker. These markers typically include the interfaces detected on seismic data. Traditionally, well data have been treated as fixed, known measurements, or at least relatively so compared to the noisy seismic data. However, with the aid of modern computers, seismic processing is more reliable and the signal to noise ratio is improved. At the same time, well technology has caused a major increase in the number of deviated and deep (5 km depth) wells. The measured positions of wells are then less reliable. This means that the well marker data cannot be treated as fixed, known geographical positions, simply used to scale the seismic data from time to depth domain. Nowadays, the uncertainties of well marker positions logged while drilling and vary according to the equipment used. This has improved the risk analysis during drilling operations. The main limitation of current technology is including the well marker position and position accuracy into the broader picture of three dimensional positioning. This entails integrating the geographical reference interfaces in east, north, depth coordinates from well markers with the seismic reflection data. Wells are sparse (10-50 wells per oil field) and carry little information about the lateral continuity of a reservoir. Seismic data, on the other hand, are abundant and laterally informative, but are not directly comparable at the well marker east, north, depth scale.
Optimal methods for integrating diverse data at a common scale are known. This is text book statistics, in broad terms referred to as least squares estimation. Tools for representing seismic data in east, north and depth coordinates and integrating these data with geographical well marker data have been lacking, particularly at the level where one can deduce the three dimensional positioning uncertainty. The traditional way of updating is in the vertical direction. For almost flat horizons, this gives a reliable method but, for dipping layers, curved surfaces or faults, this can introduce bias. Methods for orthogonal shifting of dipping surfaces have been proposed, but this is still an ad-hoc technique that does not capture intrinsic direction variability that can actually be physically modelled using, for instance, ray-tracing. Moreover, consistent assessment of uncertainties is important to make fast decisions in high dimensional reservoir systems. The current state of the art is driven by a search for the ‘best’ structural model, without controlling the data going into the estimation. Hence, updating the geographical model is by current standards a tedious process with too much work being done on reiterating the data and trying to match information that cannot be unified.
EP1306694 discloses a method of combining first and second models of a common region of space, such as a region of the earth below the surface, to form a third model. Common points have different positions in the first and second models. A predetermined correlation exists between the positions of the common points in the first model and the positions of points of interest in the first model. The positions of the common points in the third model are derived from the common point positions in the first and second models. The positions in the third model of the points of interest are derived from the positions of the common points in the third model and from the predetermined correlation.
GB 2352746A discloses a method of producing impact point position probability maps for a well. A fixed target point is defined at an initial location of a surface with the aid of a grid composed of nodes and of grid cells. An uncertainty vector is assigned to each node and is determined by applying a Monte-Carlo statistical method. When the values for all nodes have been calculated, a resulting occurrence of location is found. A target point is projected onto each occurrence of location so as to determine a point of impact. The distribution for the set of input points is transferred to the surface and the density of the impact points gives the probably that any point of the surface is a point of impact. The probability density is mapped as level curves.
GB2325523A discloses a method of producing maps of the risks in positioning a well in an environment. The method uses a first interpreted horizon extracted from a seismic block migrated with at least a first value of velocity including a velocity uncertainty. A second interpreted horizon is formed by migration of the first horizon using a second value of the velocity equal to the first value plus the uncertainty. A third interpolated horizon is formed by migration of the first horizon using a third value of velocity equal to the first value minus the uncertainty. A positioning point for the well is selected on the first horizon and a vertical is plotted which passes through the point and intersects the second and third horizons at migrated points. On the second interpreted horizon, the positions are determined corresponding to the migrated points, the first portion of the interpreted horizon located between the said positions constituting the locus of the potential positions of the well for the uncertainty.
WO97/38330 discloses a 3-D geological modelling technique.
US 2004/0220789A1 discloses a method of calculating meshed realisations of a hydrocarbon reservoir.
According to a first embodiment of the invention, there is provided a method of forming a geological model of a region of the Earth, comprising the steps of:
“i.” providing seismic data obtained from the region and including seismic travel time uncertainty;
“ii.” providing a seismic velocity model of the region including velocity uncertainty;
“iii”. performing image ray tracing on the seismic data using the velocity model to determine the three dimensional positions of a plurality of points of the region;
“iv.” calculating three dimensional positional uncertainties of at least some of the points from the travel time uncertainty, the velocity uncertainty and uncertainty in ray propagation direction; and
“v.” combining the positions determined in the step “iii” with the uncertainties calculated in the step “iv” to form a first geological model.
At least some of the points may be disposed at at least one interface, identified from the seismic date, between sub-regions of the region of different seismic velocities.
At least some of the points may be disposed at faults identified from the seismic data.
The travel time uncertainty may be determined from the seismic wavelength used to obtain the seismic data.
The velocity uncertainty may be determined from knowledge of the geology of the region.
The step “iii” may comprise determining the position of each of the points as a function of: the position at a shallower interface where a ray incident at the point intersects the shallower interface: the seismic velocity from the position to the point obtained from the velocity model; and the travel time from the position to the point obtained from the seismic data. The step “iv” may comprise differentiating the function. The function may include a first sub-function representing Snell's law and a second sub-function representing dip at the position and the step “iv” may comprise determining the derivatives of the first and second sub-functions.
The step “v” may include assigning correlations among at least some of the points.
The method may further comprise assigning correlations among velocity values in the velocity model.
The method may comprise the further steps of:
“vi” providing non-seismically obtained three dimensional position data and three-dimensional positional uncertainty data about the region; and
“vii” adjusting the first geological model by means of the data provided in the step “vi” to obtain a second geological model. The non-seismically obtained data may comprise well marker data.
The step “vii” may comprise selecting at least one common point of the region which is common to the first geological model and to the non-seismically obtained data and determining the position and the positional uncertainty of the common point in the second geological model from the positions and the positional uncertainties of the common point in the first geological model and in the non-seismically obtained data. The at least one common point may represent common or adjacent geological features. The at least one common point may represent a location on one interface in the first geological model and a location in the non-seismically obtained data where a well passes through the interface. The step “vii” may comprise moving the location of the common point in the first geological model substantially parallel to a ray path at or adjacent the location.
The at least one common point may represent a location on a fault in the first model and a location in the non-seismically obtained data where a well passes through the fault. The step “vii” may comprise moving the location of the common point in the first geological model substantially perpendicularly to the fault surface.
The method may further comprise updating the non-seismically obtained data by moving the location of the common point in the non-seismically obtained data in a direction substantially opposite the direction of movement in the first geological model.
The step “vi” may comprise providing non-seismically obtained velocity data and velocity uncertainty data about the region. The method may further comprise forming and/or updating the velocity model in accordance with the non-seismically obtained velocity and velocity uncertainty data.
The step “vii” may be performed with a constraint that interface/fault intersections are preserved in the second geological model.
The step “vii” may comprise selecting a plurality of common points and adjusting the first geological model in a single step.
The step “vii” may comprise adjusting the first geological model in a first step, in respect of the at least one common point on the interface, and then in a second step, in respect of the at least one common point on the fault.
The step “vii” may comprise adjusting the first geological model recursively layer by layer.
According to a second embodiment of the invention, there is provided a computer program arranged to program a computer to perform a method according to the first aspect of the invention.
According to a third embodiment of the invention, there is provided a computer containing or programmed by a program according to the second aspect of the invention.
According to a fourth embodiment of the invention, there is provided a computer-readable storage medium containing a program according to the second aspect of the invention.
According to a fifth embodiment of the invention, there is provided transmission of a program according to the second aspect of the invention.
According to a sixth embodiment of the invention, there is provided a method of drilling a bore in a region of the earth, comprising performing a method according to the first aspect of the invention and controlling drilling in accordance with the geological model.
It is thus possible to provide a technique which provides improved knowledge of the geology of a region of the earth. This may be used, for example, to allow better decisions about drilling and drainage strategies to be made.